Do you want to know what will happen in the future? To gain true predictive insight, skip the tea leaves and look toward your data. SAS instructor Jeff Thompson is a high-energy data mining expert who will be demonstrating how to gain predictive insight from your data in his new
I just returned home from an expedition/adventure boat trip to Cuba, and Talk Like a Pirate day is coming up this Saturday - what a combination for an interesting blog! I hope you enjoy a few pictures, and a bit of data analysis on these topics! A couple of weeks ago,
Among the tightly held cards, piles of chips and bright lights, there have been stories that have unfolded in Las Vegas that have been forever preserved in time, never seeing the light of day. But what if what happened in Vegas…could be shared with excitement with your friends and family?
Suppose you wish to select a random sample from a large SAS dataset. No problem. The PROC SURVEYSELECT step below randomly selects a 2 percent sample: proc surveyselect data=large out=sample method=srs /* simple random sample */ n=1000000; /* sample size */ run; Do you have a SAS/STAT license? If not,
I think everyone can agree that being able to debug programs is an important skill for SAS programmers. That’s why Susan Slaughter and I devoted a whole chapter to it in The Little SAS® Book. I don’t know about you, but I think figuring out what’s wrong with my program
The digital disruption phenomenon is redrawing the market map. New players, products and services are gaining competitive advantage, while traditional business and revenue models are being questioned. Gartner believes that by 2020, thanks to the Internet of Things, information will be used to reinvent, digitalize or eliminate 80% of business
The 2015 United States Tennis Open tournament is now underway, and like most tennis fans, I’ve got my eyes on women’s tennis great Serena Williams, as she attempts to make history by winning the tournament and achieving a calendar Grand Slam. What are her chances of reaching the milestone? Most
This post is the third and final in a series that illustrates three different solutions to "flattening" hierarchical data. Don't forget to catch up with Part 1 and Part 2. Solution 2, from my previous post, created one observation per header record, with detail data in a wide format, like
I was recently asked why I would recommend my new class, Explaining Analytics to Decision Makers: Insights to Action. The answer goes back to some great advice, a lunch of eggplant parmesan and in another more twisted way, to what was ironically affectionately known as the “bomb plant.” Early in
In a little more than two weeks, I will be in one of my favorite places, San Diego, California, recruiting potential SAS Press authors at the JMP Discovery Summit, which will be held at the beautiful Paradise Point Resort and Spa from 14 September to 17 September 2015. I’m especially
